Senior Director of AI, Data & Enterprise Architecture

Sourceo; Singapore; On-site; SGD 180,000 - 260,000; Full time

Benefits offered by this job

Health & wellness benefits

Training programs

Internal mobility

Job summary

Singtel is seeking a Senior AI Data and Enterprise Architect/Director to design and govern enterprise-wide architecture for trusted data, scalable analytics, and production-grade AI including ML and GenAI.

You will align business strategy with technology platforms, define target-state architectures, roadmaps, and reference patterns across data platforms, AI/ML lifecycle, integration, security and governance, while partnering with leaders across the organization to ensure reliable, explainable AI

Qualifications

• Bachelor’s degree in computer science, engineering, information systems, or related field.
• 10-12+ years of experience in enterprise/data/platform architecture.
• Proven experience designing modern data platforms (Lakehouse/warehouse).
• Strong understanding of AI/ML deployment architectures including MLOps.
• Experience with cloud platforms (AWS/Azure/GCP) and cloud-native tools.

Responsibilities

• Lead end-to-end architecture for enterprise data and AI capabilities.
• Define target-state architectures, roadmaps, and standards.
• Architect patterns for data, AI/ML, GenAI, and integration.
• Partner with business, product, engineering, security for alignment.
• Mentor architects and drive capability maturity across the organization.

Skills

MLOps

Data architecture

Enterprise architecture

Cloud architecture

Stakeholder communication

Security & privacy

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems

Tools

Kubernetes

AWS/Azure/GCP

Job description

Singtel is seeking a Senior AI Data and Enterprise Architect/Director to design and govern enterprise-wide architecture for trusted data, scalable analytics, and production-grade AI including ML and GenAI.

You will align business strategy with technology platforms, define target-state architectures, roadmaps, and reference patterns across data platforms, AI/ML lifecycle, integration, security and governance, while partnering with leaders across the organization to ensure reliable, explainable AI